Articles, Tech Tips, Case Studies

Categories

The High Cost of Fraud

Tips for Testing Common Schemes Using IDEA

Fraud costs are on the rise…again. More than 23% of occupational fraud cases resulted in a loss of at least $1 million. When owners or executives committed fraud, the median damage was more than 10 times worse than when employees were the perpetrators. 1

Most frauds are detected through tips, rather than internal or external auditors. There is probably a good explanation for that, considering expanding data volumes and the complexity of information that needs to be analyzed. Regardless, there is little tolerance when errors and fraud go undetected.

Using the right tools and knowing where to look are critical. Relevant information resides in financial files within the organization. The larger and more detailed the data files are, the more useful data analysis becomes.

The median loss from a single occupational fraud in the U.S. is $120,000.Source: Association of Certified Fraud Examiners (ACFE)
2016 Report to the Nations

IDEA 10 has some built-in features to help sift through vast amounts of data to uncover anomalies and outliers that may indicate fraud. If you haven’t upgraded to IDEA 10, you are missing out on some key audit intelligence features that are now available including:

Discover – Identifies trends, patterns and outliers, and creates a dashboard to further refine the data based on your specific needs

Visualize – Helps interpret and monitor data trends in a single or multiple databases

The visualization of the data is key for those that aren’t in the IT world and may not understand how databases are set up. Numbers don’t speak to them as they do to others. Seeing things visually is invaluable.Aaron Boor, CISA, IT Audit & Project Automation Manager, Donegal Insurance Group

Advanced Fuzzy Duplicate – Identifies multiple similar records using up to 3 character fields, then groups them based on the degree of similarity to detect data entry errors, multiple data conventions for recording information and fraud

Fraud Risk Assessment Steps

Build a profile of potential frauds to be tested

Analyze data for possible indicators of fraud

Automate the detection process through continuous
auditing/monitoring of high-risk business functions to improve controls

Investigate and drill down into emerging patterns

Expand scope and repeat as necessary

Report

Start where the fraudsters start – where the money is. Here are some key areas and analytics to use to identify commonly-used fraud schemes:

Payroll Fraud Schemes
While most payroll frauds are found by accident, data analysis can be used on a regular basis to analyze payments and search for outliers simply by matching payments to the payroll master file. Often fictitious or “ghost” employees are set up on a salary system to receive automatic payments.

Data to Gather:

Payroll master file with cumulative totals and static data

Monthly transactions file

Employee data including Social Security numbers, address, employee number

Data Analysis Tests to Perform:

Test for duplicate employees on the entire payroll file (appending or joining payroll files if necessary) using the employees’ SSNs as a unique employee identifier

Check for duplicate bank accounts [Note: False positives may include family accounts where more than one family member is employed by the organization]

Identify employee accounts with excessive credit memos, or large deposits

Match master information from the payroll file with the organization’s personnel file to determine whether there are “ghost” employees on the payroll

Compare the payroll file using two dates (beginning and end of the month) to determine whether new hires and terminations are represented as expected, and if any employees have received unusually large salary increases

View employee salaries by minimum and maximum by position and/or level. Also test allowances by position and level

Check for excessive overtime and allowance claims

Compare holidays/vacation and sick leave against limits by position/level

Match termination dates against the final few paychecks – look for scheme where extra checks were issued and diverted to the clerk’s account

Purchase Frauds
Purchase frauds are prevalent, mainly because there are so many ways a potential fraudster can work the system to their advantage. Dummy invoices, reuse of valid invoices and withholding of credit notes are just a few examples of purchasing frauds. Many frauds involve the manipulation of the payments information on personal accounts within the AP system. Examples of this include:

Creation of a fictitious supplier in the general ledger

Creation of a fictitious branch within a genuine supplier

Reactivating a dormant account

Miscellaneous accounts are particularly vulnerable, and don’t overlook frauds perpetuated on a genuine suppliers account without their knowledge. Accounts with high levels of transactions are susceptible to fraud because fictitious items can easily be buried.

Data to Gather:

Complex purchasing systems with automatic reordering capabilities are also a target. Once a supplier has been set up, or a requisition is input, payments are processed automatically. IDEA can be used on multiple files to test for fraud including

Supplier master

Purchase ledger

Payments history

Purchase invoices

Supplier Master File

Using the first 5-6 characters of the name, match supplier names against a list of employee surnames from the payroll or personnel file

Test for accounts without VAT numbers or duplicate VAT numbers

Examine purchase ledger transactions for entries at or just below the management approval level – if the system finds the approving authority for a transaction, examine the value distribution for each manager

Test to see if amounts are being approved just above or below break points in authority level by a value distribution across the whole ledger

Search for split invoices to enable approvals by an individual

Extract all invoices within 90% of an approved limit and search for all invoices from that supplier. Next, sort by approving manager, department, and date to identify possible split invoices or summarize payments by invoice number to determine how many partial payments have been made for each invoice.

Test for duplicate invoices using value and supplier codes as key fields for one test, and purchase order number for another. The 2nd processing of invoices can be used to establish a value on the purchase ledger to make a fraudulent payment.

Identify invoices without a valid purchase order or from unapproved vendors

Find invoices with more than one purchase order authorization

Identify multiple invoices with the same item description

Extract vendors with duplicate invoice numbers

Find invoice payments issued on non-business days, such as weekends or holidays

Identify multiple invoices just under approval cut-off levels

Payments

Search the payments file for payees without “Inc”, “LLC” and LTD” in their names to identify payments to individuals

Stratify the size of payments to extract any exceptionally high payments

If payments are made by electronic transfers, extract lists of bank codes and account numbers from both the P/L payments files and the payroll – compare to see if any accounts match

Compare voucher or invoices posted against purchase order amounts

Many of these tests can be automated, and if you need assistance with creating a script, contact us at services@audimation.com. We also welcome your questions and provide live, step-by-step assistance at no cost to supported IDEA users – simply contact the IDEA Help Desk at 888.641.2800 and select option 4 or email us at helpdesk@audimation.com.

Consider scope to be a building in which people work. The tools required to accomplish their tasks will of course be housed in that building, but in scripting it’s important to determine which tools need to be shared among the buildings.